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Estimating Rice Agronomic Traits Using Drone-Collected Multispectral Imagery

Dimitris Stavrakoudis, Dimitrios Katsantonis, Kalliopi Kadoglidou, Argyris Kalaitzidis, Ioannis Gitas
2019 Remote Sensing  
This paper presents empirical models for predicting agronomic traits that are relevant to yield and N requirements of rice (Oryza sativa L.) through remotely sensed data.  ...  Multiple linear regression models were constructed at key growth stages (at tillering and at booting), using as input reflectance values and vegetation indices obtained from a compact multispectral sensor  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
doi:10.3390/rs11050545 fatcat:dsbhaxc7xba4hhbbcbnojrjybe

Effect of the Solar Zenith Angles at Different Latitudes on Estimated Crop Vegetation Indices

Milton Valencia-Ortiz, Worasit Sangjan, Michael Gomez Selvaraj, Rebecca J. McGee, Sindhuja Sankaran
2021 Drones  
data acquired using an unmanned aerial vehicle (UAV).  ...  The pea and chickpea breeding materials were evaluated in a high latitude (46°36′39.92″ N) zone, whereas the rice lines were assessed in a low latitude (3°29′42.43″ N) zone.  ...  Drones 2021, 5, 80  ... 
doi:10.3390/drones5030080 fatcat:ac27fmn5fbbwvawavntjqsik3i

Using Remote Sensing and an Unmanned Aerial System for Weed Management in Agricultural Crops: A Review

Muhammad Huzaifah Mohd Roslim, Abdul Shukor Juraimi, Nik Norasma Che'Ya, Nursyazyla Sulaiman, Muhammad Noor Hazwan Abd Manaf, Zaid Ramli, Mst. Motmainna
2021 Agronomy  
The integration of drones, artificial intelligence, and various sensors, which include hyperspectral, multi-spectral, and RGB (red-green-blue), ensure the possibility of a better outcome in managing weed  ...  This review provides an overview of the potential and practical use of unmanned aerial vehicle and remote sensing techniques in weed management practices and discusses how they overcome future challenges  ...  Acknowledgments: The authors are grateful to the Research Project entitled "Pest and Disease Monitoring Using Artificial Intelligent for Risk Management of Rice Under Climate Change" under the Long-Term  ... 
doi:10.3390/agronomy11091809 fatcat:wt5aasqwhzbgznqfwp6d34qabq

Remote and Proximal Assessment of Plant Traits

Ittai Herrmann, Katja Berger
2021 Remote Sensing  
The inference of functional vegetation traits from remotely sensed signals is key to providing efficient information for multiple plant-based applications and to solve related problems [...]  ...  The research was also supported by the Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology  ...  UAV scale of symptom severity Ag (olive groves) local stands (leaf-and canopy level) UAV, multispectral (DJI Mavic Pro drone with a four-band multispectral camera) non- parametric  ... 
doi:10.3390/rs13101893 fatcat:ccl64hutnzbupn54lqlosecjvu

Review on unmanned aerial vehicles, remote sensors, imagery processing, and their applications in agriculture

Daniel Olson, James Anderson
2021 Agronomy Journal  
biotic stress tolerance, which can greatly expedite field data collection for advancing germplasm with desired agronomic traits.  ...  UAV technologies also offers researchers with a non-destructive, objective manner for obtaining phenotypic measurements such as height assessment, biomass estimation, canopy reflectance, and abiotic and  ...  Estimation Of soil moisture at different soil levels using machine learning techniques and Unmanned Aerial Vehicle (UAV) Multispectral Imagery.  ... 
doi:10.1002/agj2.20595 fatcat:pulgc4epnrfezfr23a6z2pvdcu

Drones for Biodiversity Conservation and Ecological Monitoring

Kristy Zhang
2019 Figshare  
Drones for Biodiversity Conservation and Ecological Monitoring  ...  Acknowledgments: We thank the Parrot Innovation Grant for the provision of the multispectral camera and the use of the Pix4D software.  ...  Special thanks to DigitalGlobe and Esri for inkind contribution and support with satellite imagery and GIS software.  ... 
doi:10.6084/m9.figshare.11322092.v1 fatcat:lzjshsnscnb2pnnn6j4k5vfejy

UAVs for Vegetation Monitoring: Overview and Recent Scientific Contributions

Ana I. de Castro, Yeyin Shi, Joe Mari Maja, Jose M. Peña
2021 Remote Sensing  
Three general categories were considered: (1) sensors and vegetation indices used, (2) technological goals pursued, and (3) agroforestry applications.  ...  The general goal was proposing UAV-based technological solutions for a better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits.  ...  A ML approach was also employed by Colorado et al. (2020) [30] to monitor canopy N in rice crops with multispectral UAV imagery.  ... 
doi:10.3390/rs13112139 fatcat:zbirrq37cjgxbpo5zooplm2jra

High-Throughput Phenotyping and Random Regression Models Reveal Temporal Genetic Control of Soybean Biomass Production

Fabiana Freitas Moreira, Hinayah Rojas de Oliveira, Miguel Angel Lopez, Bilal Jamal Abughali, Guilherme Gomes, Keith Aric Cherkauer, Luiz Fernando Brito, Katy Martin Rainey
2021 Frontiers in Plant Science  
A subset of the SoyNAM population (n = 383) was grown in multi-environment trials and destructive AGB measurements were collected along with multispectral and RGB imaging from 27 to 83 days after planting  ...  Narrow-sense heritabilities estimated over time ranged from low to moderate (from 0.02 at 44 DAP to 0.28 at 33 DAP).  ...  ACKNOWLEDGMENTS We express our gratitude to the soybean breeding laboratory at Purdue for their assistance in the field work, and Stuart Smith for his contributions to managing the UAS imagery.  ... 
doi:10.3389/fpls.2021.715983 pmid:34539708 pmcid:PMC8446606 fatcat:kcgvbdqlqfhb5gq27bdehd7ohu

Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature

Jian Wang, Bizhi Wu, Markus V. Kohnen, Daqi Lin, Changcai Yang, Xiaowei Wang, Ailing Qiang, Wei Liu, Jianbin Kang, Hua Li, Jing Shen, Tianhao Yao (+3 others)
2021 Plant Phenomics  
Thus, we developed a low-cost, high-throughput phenotyping and nondestructive method by combining UAV-based hyperspectral measurements and machine learning for estimation of rice yield to improve rice  ...  In this study, we developed an accurate large-scale approach and presented the potential usage of hyperspectral data for rice yield measurement using the XGBoost algorithm to speed up the rice breeding  ...  Acknowledgments The authors acknowledge the help from Pengfei Gao, Kaiqiang Hu, Kai Chen, and Yubang Gao from Lianfeng Gu's group during data collection.  ... 
doi:10.34133/2021/9765952 pmid:33851136 pmcid:PMC8028843 fatcat:fb2alxovr5grtm2nt2sjczdiqy

Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

Vanesa Martos, Ali Ahmad, Pedro Cartujo, Javier Ordoñez
2021 Applied Sciences  
These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible.  ...  Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs),  ...  biochemical plant traits were reported, highlighting the importance of drone imagery for centimeter-scale characterization [4] .  ... 
doi:10.3390/app11135911 fatcat:txvdhn73ynbwlffad6nufw7nki

QTL Mapping of Leaf Area Index and Chlorophyll Content Based on UAV Remote Sensing in Wheat

Wei Wang, Xue Gao, Yukun Cheng, Yi Ren, Zhihui Zhang, Rui Wang, Junmei Cao, Hongwei Geng
2022 Agriculture  
Clarifying the feasibility and effectiveness of high-throughput phenotypic data obtained from UAV multispectral images in gene mining of important traits is an urgent problem to be solved in wheat.  ...  Then, on the basis of the normalized difference vegetation index (NDVI) and green normalized difference vegetation index (GNDVI), which were determined by multispectral imagery, the LAI and CC were comprehensively  ...  [16] used the UAV multispectral imagery-based green normalized difference vegetation index (GNDVI) to estimate wheat LAI by remote sensing and obtained good prediction (R 2 = 0.85). Singhal et al.  ... 
doi:10.3390/agriculture12050595 fatcat:kbfllafsebd27g5msm6dzaoq4a

Remote Sensing and Machine Learning in Crop Phenotyping and Management, with an Emphasis on Applications in Strawberry Farming

Caiwang Zheng, Amr Abd-Elrahman, Vance Whitaker
2021 Remote Sensing  
Simultaneous use of multiple sensors (e.g., high-resolution RGB, multispectral, hyperspectral, chlorophyll fluorescence, and light detection and ranging (LiDAR)) allows a range of spatial and spectral  ...  resolutions depending on the trait in question.  ...  ), biophysical (e.g., LAI and biomass), and biochemical (e.g., chlorophyll and nitrogen content) traits of agronomic crops, fruit trees, and vegetables.  ... 
doi:10.3390/rs13030531 fatcat:yts5pbuq2zhwrm6rt6c6hmkyti

UAS-Based Plant Phenotyping for Research and Breeding Applications

Wei Guo, Matthew E. Carroll, Arti Singh, Tyson L. Swetnam, Nirav Merchant, Soumik Sarkar, Asheesh K. Singh, Baskar Ganapathysubramanian
2021 Plant Phenomics  
These advantages have expanded the use of UAS-based plant phenotyping approach in research and breeding applications.  ...  This paper reviews the state of the art in the deployment, collection, curation, storage, and analysis of data from UAS-based phenotyping platforms.  ...  Ongoing research seeks to obtain more information per pixel using these strategies [207] [208] [209] , which will enable more traits to be estimated with better granularity.  ... 
doi:10.34133/2021/9840192 fatcat:2jn6v4mscvf7dh355dof376tgm

High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement

Sumit Jangra, Vrantika Chaudhary, Ram C. Yadav, Neelam R. Yadav
2021 Phenomics  
High-throughput phenotyping techniques and platforms help unraveling the genetic basis of complex traits associated with plant growth and development and targeted traits.  ...  Development of user-friendly data management tools and softwares to better understand phenotyping will increase the use of field-based high-throughput techniques, which have potential to revolutionize  ...  Several agronomic traits such as moisture content, lodging, tiller density, and biomass can be measured using this multi-sensor platform (Busemeyer et al. 2013 ). 4.  ... 
doi:10.1007/s43657-020-00007-6 fatcat:kfqiivoas5hsjkjbfcha5546vq

Translating High-Throughput Phenotyping into Genetic Gain

José Luis Araus, Shawn C. Kefauver, Mainassara Zaman-Allah, Mike S. Olsen, Jill E. Cairns
2018 Trends in Plant Science  
Field phenotyping must be integrated into a wider context than just choosing the correct selection traits, deployment tools, evaluation platforms, or basic data-management methods.  ...  platform using a multispectral camera.  ...  For example, the rate of manual measurements of plant height in rice (Oryza sativa L.) has been estimated at 45 plots per hour, compared with 3000 plots per hour using a phenomobile equipped with an ultrasonic  ... 
doi:10.1016/j.tplants.2018.02.001 pmid:29555431 pmcid:PMC5931794 fatcat:ydvyq5oakjh4li7uo7644w2klq
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